Path planning algorithm based on optimize and improve RRT and artificial potential field

被引：0
作者：
Xin P. [1 ]
Wang Y. [1 ,2 ]
Liu X. [1 ]
Ma X. [1 ]
Xu D. [2 ]
机构：
[1] Key Laboratory of Intelligent Industrial Equipment Technology of Hebei Province, School of Mechanical and Equipment Engineering, Hebei University of Engineering, Handan
[2] Hebei Provincial Technological Innovation Center for High Quality Cold Heading Steel, Hebei University of Engineering, Handan
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2023年 / 29卷 / 09期
关键词：
fusion algorithm; improve artificial potential field; improve dynamic window approach; obstacle avoidance; optimize and improve rapidly random tree algorithm;
D O I：
10.13196/j.cims.2023.09.003
中图分类号：
学科分类号：
摘要：
Aiming at the disadvantages of traditional Rapidly Random Trcc(RRT) algorithm in planning path, such as large randomness, low search efficiency, and the planned path is not conducive to robot movement, the improvement was made from three directions. For the problem of large randomness in the random tree expansion, the traditional expansion direction was added into the improved artificial potential field method to make the random tree grow in favor of the target point. Key points were extracted from the path planned of the improved RRT algorithm, and the path was optimized. The optimized path was segmented according to the key points using the improved evaluation function dynamic window method. Experiments showed that the optimized and improved RRT algorithm was better than the traditional A∗ algorithm and the traditional RRT algorithm in terms of path length, path planning time and inflection point, etc. The path planned by the fusion algorithm in complex environment could well avoid obstacles, and the path was smoother and shorter. © 2023 CIMS. All rights reserved.
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页码：2899 / 2907
页数：8
相关论文
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